Paper: SSA-UO: Unsupervised Sentiment Analysis in Twitter

ACL ID S13-2083
Title SSA-UO: Unsupervised Sentiment Analysis in Twitter
Venue Joint Conference on Lexical and Computational Semantics
Year 2013

This paper describes the specifications and re- sults of SSA-UO, unsupervised system, pre- sented in SemEval 2013 for Sentiment Analy- sis in Twitter (Task 2) (Wilson et al., 2013). The proposal system includes three phases: data preprocessing, contextual word polarity detection and message classification. The preprocessing phase comprises treatment of emoticon, slang terms, lemmatization and POS-tagging. Word polarity detection is car- ried out taking into account the sentiment as- sociated with the context in which it appears. For this, we use a new contextual sentiment classification method based on coarse-grained word sense disambiguation, using WordNet (Miller, 1995) and a coarse-grained sense in- ventory (sentiment inventory) built up from SentiWordNet (Baccianella et al., 2010). Fi-...